Grant: CIHR Fellowship

Obesity is a major health concern and a risk factor of type-2 diabetes, hypertension, and heart disease. Genetic factors influence body weight and can explain up to 70% of the inter-individual variation of body mass index (BMI). In some cases, mutations in only one gene are thought to cause obesity (i.e monogenic obesity); and in others, many different genetic factors contribute to the development of obesity (i.e polygenic obesity). Although many genetic mutations/variants have been implicated in obesity, it is still a challenge to categorize them into those that are truly "causal" and those whose function is conditional on other variants and/or environmental factors. I aim in my study to 1) calculate for each known mutation the probability that a person develops obesity if he/she is a carrier. This task was previously limited by the absence of large population datasets. I will conduct my analyses in the largest whole genome sequencing dataset, TOPMed (N > 65k individuals) as well as the Mount Sinai's biobank which has > 35k samples with sequencing data. I will also 2) seek to discover new genetic variants that influence BMI and obesity using linear and logistic regression. I will focus on genetic variants that are predicted to disrupt protein function: protein truncating variants (PTVs) and damaging missense variants. PTVs are genetic variants that lead to shortening of the protein-coding sequence of genes and are highly predicted to cause loss-of-function of a given protein. Previous work on PTVs led to therapeutic advances. We will attempt to identify novel PTVs associated with obesity and explore whether an accumulation of PTVs and/or damaging missense variants in certain genes influences obesity. We have access to two large sequencing datasets which provides the best opportunity to explore our hypotheses. This work will contribute a better understanding of the mechanisms involved in obesity and may provide new gene-based drug targets to personalize treatment.